import numpy as np
from sklearn import metrics


y_true = np.array([1, 0, 0, 1])
y_pred = np.array([0, 0, 0, 0])


def mse_loss(y_true, y_pred):
    return (y_true - y_pred ** 2).mean()


print(metrics.mean_squared_error(y_true, y_pred))
print(mse_loss(y_true, y_pred))
